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Ecological Factors Shaping Marine Actinobacterial Niches in Diverse Coastal Habitats of the Andamans Sea, India

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Rajagopal Gobalakrishnan and Kannan Sivakumar

Submitted: 10 January 2024 Reviewed: 27 February 2024 Published: 29 October 2024

DOI: 10.5772/intechopen.1004862

Advances in Coastal Ecology IntechOpen
Advances in Coastal Ecology Processes, Patterns, and Services Edited by Thomas Trott

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Advances in Coastal Ecology - Processes, Patterns, and Services

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Abstract

Marine microbial communities are structured by the spatial temporal, variability of physico-chemical, and biotic parameters. These parameters form a useful tool for the ecological assessment and monitoring of coastal ecosystems. The present investigation aims to study the influence of the physico-chemical parameters on the distributional variations of culturable actinobacterial population density, at six different locations on the Havelock Island coast of the Andamans, India. The study covered the important parameters viz. temperature in air (29–23°C), surface water (26–24°C), sediments (27–23°C), salinity in water (18–35 psu), sediments (17–34 psu), pH in water (6–8) and sediments (7.6–8.7), dissolved oxygen (DO) (4.60–2.10 ml l−1), electrical conductivity (EC) (2–5.5 dS m−1), nitrogen (N) (0.55–8 mg g−1), potassium (K) (2.63–10.88 mg g−1), phosphorus (P) (4.50–3.13 mg g−1), total organic carbon (TOC) (60.88–11.88 mg g−1), sand (65–95%), silt (3.5–9.4%), and clay (1.2–30%). Culturable actinobacterial population density in the sediments ranged from 8 × 103 to 21 × 103 CFU g−1, registering the higher value at station 4 (mangrove) and the lower value at station 3 (beach). Cluster and principal component analysis (PCA) results have revealed that the mangrove environment favors a higher density of actinobacteria than the coral, seagrass, and beach habitats of the Island.

Keywords

  • actinobacteria
  • Havelock Island
  • mangroves
  • microbial ecology
  • physico-chemical characters

1. Introduction

An ecosystem comprises the collective presence of organisms inhabiting a particular region, alongside the non-living elements of the environment, including air, soil, and water, that interact with these organisms. Especially, marine ecosystems are dynamic with valuable natural resources and are the largest among the Earth’s aquatic systems. They have important environmental values and their destruction will affect the whole marine environment [1]. Therefore, the study regarding the physico-chemical properties of the coastal environment is very essential.

Mostly the marine ecosystem is fueled by the regeneration of nutrients, mediated by the marine microbes and these are key to the decomposition of organic matter and the reformation of nutrients, thereby determining the productivity of an ecosystem [2]. Microorganisms inhabit every corner of the ocean, with diverse habitats ranging from open waters, sediments, and the bodies of marine organisms to estuaries and hydrothermal vents [2], and they play a crucial role in marine processes, actively participating in the transformation and mineralization of organic materials within both sediments and overlying waters [3].

The structure of microbial communities is shaped by the temporal and spatial fluctuations of physico-chemical and biotic parameters. The distribution, diversity, and activities of microorganisms are influenced by a multitude of hydro-biological factors and nutrient levels present in the aquatic environment. Extensive research has been conducted in the marine environment to thoroughly investigate these relationships [4, 5]. The distribution of microbial diversity depends on changes in water and other physico-chemical parameters [6]. They play important roles in maintaining the ecosystems and replaying lay to environmental changes and anthropic activities [7]. In comparison to other benthic organisms, microbial communities exhibit remarkably rapid responses to environmental and pollution changes. Moreover, the fate of the coastal marine sediment deposits is entirely dependent on the activities of these microorganisms [8, 9].

For almost two decades, actinobacteria have been considered an important constituent of the microbial communities in marine ecosystems [10], particularly in marine sediments, where they can reach up to 13% of the bacterial abundance [11, 12, 13, 14]. Actinobacteria are very widely distributed in the world’s oceans and truly indigenous marine actinobacteria have now been described [15]. They play pivotal ecological roles in the carbon cycle with their capability to break down organic materials and recycle them as done by their terrestrial counterparts [16]. Exploration of marine actinobacteria will not only address fundamental questions in microbial ecology but also yield valuable insights for harnessing their biotechnological potential. However, there are still numerous unanswered queries concerning the ecological roles of actinobacteria in marine environments, as well as their distribution patterns and evolutionary origins. There is a growing recognition that marine actinobacteria represent a significant reservoir for the exploration and discovery of novel secondary metabolites with great potential for biotechnological applications [17].

The combined analysis of water and sediment physico-chemical characteristics serves as a powerful approach for ecologically assessing and monitoring diverse coastal ecosystems. Key factors, such as temperature, salinity, dissolved oxygen, and sediment properties, collectively exert significant influence on the abundance and distribution of benthic organisms. It is important to note that no single factor alone holds a dominant impact, as these variables operate in conjunction to shape the ecological dynamics [18, 19]. To ensure the high quality of coastal water resources, it is essential to assess the pollution loads by monitoring a range of physico-chemical parameters [20]. In light of this, the objective of the present study was to investigate how variations in the distribution of culturable actinobacterial population density in the coastal region of Havelock Island, Andamans, are influenced by these physico-chemical parameters.

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2. Materials and methods

2.1 Study area

The Andaman group of islands is situated in the Bay of Bengal, spanning between latitude 11°97′N and longitude 93°00′E. For this study, Havelock Island, encompassing mangrove, coral, seagrass, and beach habitats, was chosen. The selection of sampling stations around this island was based on the various habitats present (Table 1 and Figure 1).

S. NoStationsLocationHabitatsCoordinates
1Station 1Boat jettyMangrove12°02′27.9″N 92°58′41.5″E
2Station 2EL DoradoCoral12°01′31.6″N 93°00′13.8″E
3Station 3Dive IndiaBeach12°01′38.5″N 93°00′15.8″E
4Station 4KalapatharMangrove11°57′37.9″N 93°00′46.6″E
5Station 5Silver sandSeagrass12°00′36.1″N 93°00′31.0″E
6Station 6Radha NagarBeach11°59′04.2″N 92°57′04.0″E

Table 1.

The sampling stations around the Havelock Island.

Figure 1.

Map showing the sampling stations in the Havelock Island.

2.2 Collection of samples

Field collections were conducted at six stations on Havelock Island to document diverse ecological characteristics (physico-chemical parameters), and collect sediment samples for actinobacteriological analysis. Using a sterile spatula, sediment samples were obtained at a depth of 25 cm from chosen locations on Havelock Island. These samples were carefully placed in sterile polythene covers and promptly transported to the field laboratory. Upon arrival, essential dilutions were prepared to facilitate subsequent microbiological analysis.

2.3 Physico-chemical parameters

Physico-chemical parameters viz. air temperature, surface water temperature, and sediment temperature were recorded using a mercury thermometer having ±0.02°C accuracy. The salinity of the water and sediments was recorded using a refractometer (Erma Company, Japan); Hydrogen-ion concentration (pH) of water was measured by a calibrated pH pen (pH Scan 1 Tester-Eutech Instruments, Singapore) and sediment pH was measured by a soil pH tester Model DM-13, Takemura Electric Works Ltd., Tokyo, Japan. Electrical conductivity (EC) was measured by Pye Unicam model 292 meters.

Water dissolved oxygen (DO) was estimated using the modified Winkler’s method, described by Strickland and Parsons [21]. Sediment samples were used for the estimation of nitrogen, phosphorus and potassium, using Kjeldahl method [22] and colorimetric method [23], in the Sugarcane Breeding Research Institute, Cuddalore. Total organic carbon (TOC) was determined using potassium chromate as an oxidizing reagent [24]. Sediment texture was assessed using the pipette method, described by Lindholem [25].

2.4 Enumeration of actinobacterial population density

To assess the population density of actinobacteria, sediment samples were obtained using a polyvinyl corer (10 cm diameter) inserted into the sediments. Prior to sampling at each station, the corer was sterilized with alcohol. The central portion of the top 2 cm of sediment samples was extracted using a sterile scoop. These sediment samples were then transferred to sterilized polythene containers and appropriately labeled. The collected sediment samples were aseptically air-dried. After 1 week, the sediment samples were blended with an equal weight of CaCO3 (1:1) and incubated at 55°C for 5 minutes [26]. The density of actinobacterial populations was determined using the spread plate method with various media viz., Kuster’s agar (KUA) [27], Starch Casein Agar (SCA) [28], Actinomycetes isolation agar (AIA) [29], Starch Casein nitrate agar (SCN) [30], and AV agar (AVA) [26]. A gram of pretreated sediment sample underwent serial dilution using sterile seawater, and 0.1 ml of each serially diluted sample was introduced onto petri plates containing the respective agar medium. The samples were spread evenly using an “L” shaped glass spreader. Subsequently, the petri plates were inverted and incubated at 37°C for 7 days. Leathery colonies of actinobacteria that emerged on the petri plates were counted from the 5th day to the 28th day. The population density of actinobacteria is expressed as colony-forming units (CFU) per gram of the sample in the text. All colonies grown on the petri plates were individually streaked and sub-cultured to ensure axenic purity and were maintained on slants [26].

2.5 Statistical analysis

A graphical representation illustrating the values of water and sediment physico-chemical parameters was generated using MS Office Excel 2007 software. Statistical analysis was conducted to explore the relationship between these parameters and actinobacterial population density, utilizing Statistical Package for Social Sciences (SPSS). Principal component analysis (PCA) and cluster analysis, implemented through Plymouth Routines In Multivariate Ecological Research (PRIMER) software, were employed to identify trends among highly correlated physico-chemical parameters and actinobacterial population density.

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3. Results

3.1 Physico-chemical parameters

Temperature (Figure 2): Air temperature varied from 29°C to 23°C, during the present period of study. The lower value (23°C) was recorded at station 5 and the higher value (29°C) was recorded at station 3. Surface water temperature varied from 26°C to 24°C, during the present study, with a lower value (24°C) at station 5 and the higher value (26°C) was recorded at stations 1, 3, and 6. Sediment temperature varied from 27°C to 23°C, registering a lower value (23°C) at station 4 and the higher value (27°C) at stations 3 and 6.

Figure 2.

Air, water and sediment temperature recorded at six stations of the Havelock Island.

Salinity (Figure 3): Water salinity fluctuated from 18 to 35 psu, during the present period of study. The lower water salinity was recorded at station 4 (18 psu) and the higher value was recorded at station 6 (35 psu). Sediment salinity fluctuated from 17 to 34 psu, with the lower value (17 psu) at station 4 and the higher value (34 psu) at stations 5 and 6.

Figure 3.

Water and sediment salinity recorded at six stations of the Havelock Island.

Hydrogen-ion concentration (pH) (Figure 4): A narrow range of fluctuation in pH of the water was exhibited and it varied from 6 to 8. The higher pH value (8) was recorded at stations 3 and 6 and the lower pH value (6) was recorded at station 1. A narrow range of fluctuation in pH of the sediments was also recorded which varied from 7.6 to 8.7, with a higher value (8.7) at station 6 and the lower value (7.6) at station 1.

Figure 4.

Water and sediment hydrogen-ion concentration recorded at six stations of the Havelock Island.

DO concentration (Figure 5): DO concentration of water ranged between 2.10 and 4.60 ml l−1. Lower value (2.10 ml l−1) at station 1 and the higher value (4.60 ml l−1) at station 5 were recorded.

Figure 5.

Dissolved oxygen concentration recorded at six stations of the Havelock Island.

EC (Figure 6): EC of the sediments fluctuated from 2 to 5.5 dS m−1, registering the lower value (2 dS m−1) at station 3 and higher value (5.5 dS m−1) at station 1.

Figure 6.

Electrical conductivity recorded at six stations of the Havelock Island.

TOC (Figure 7): Sediment TOC content exhibited wide variations at the stations investigated, registering the lower value (0.55 mg g−1) at station 6 and higher value (8 mg g−1) at station 4.

Figure 7.

Sediment total organic carbon content recorded at six stations of the Havelock Island.

Sediment nitrogen (Figure 8): Sediment nitrogen content varied from 2.63 to 10.88 mg g−1, recording the lower value at station 2 and higher value at station 4.

Figure 8.

Sediment nitrogen content recorded at six stations of the Havelock Island.

Sediment phosphorous (Figure 9): Sediment phosphorous content recorded the higher value (4.50 mg g−1) at station 3 and lower value (3.13 mg g−1) at station 4.

Figure 9.

Sediment phosphorous content recorded at six stations of the Havelock Island.

Sediment potassium (Figure 10): Sediment potassium content showed fluctuation, registering higher value (60.88 mg g−1) at station 4 and lower value (11.88 mg g−1) at station 2.

Figure 10.

Sediment potassium content recorded at six stations of the Havelock Island.

Sediment texture (Figure 11): Sediment texture in terms of sand, silt, and clay was in the range of 65–95%; 3.5–9.4%, and 1.2–30% respectively. Lower content of sand (65%) was recorded at station 4 and higher content (95%) was recorded at station 6. Lower silt content (3.5%) was noticed at station 1 and higher value (9.4%) was recorded at station 5. Clay content was lower (1.2%) at station 6 and higher (30%) at station 4.

Figure 11.

Sediment texture recorded at six stations of the Havelock Island.

3.2 Actinobacterial population density

The actinobacterial population density (Figure 12), ranged from 2 × 103 to 21 × 103 CFU g−1, with the highest density (21 × 103 CFU g−1) observed in Kuster’s agar and the lowest density (2 × 103 CFU g−1) in Actinomycetes isolation agar. Within the Kuster’s agar medium, the highest actinobacterial population density (21 × 103 CFU g−1) was noted at station 4, while the lowest density (2 × 103 CFU g−1) was observed at station 3. In Starch Casein agar medium, the highest density (17 × 103 CFU g−1) occurred at station 4, and the lowest density (3 × 103 CFU g−1) at station 3. Actinomycetes Isolation Agar medium exhibited a higher density (9 × 103 CFU g−1) at station 4 and a lower density (2 × 103 CFU g−1) at station 5. Starch Casein Nitrate Agar medium displayed a higher actinobacterial population density (14 × 103 CFU g−1) at station 4, while a lower density (5 × 103 CFU g−1) was recorded at station 6. In the AV agar medium, a higher actinobacterial population density (11 × 103 CFU g−1) was observed at station 4, with the lower density (3 × 103 CFU g−1) noted at station 3.

Figure 12.

Actinobacterial population density recorded at six stations of the Havelock Island.

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4. Discussion

In addition to the physical, biological, and chemical factors shaping microbial niches in marine sediments, hydrodynamic forces exert a significant influence, particularly in the shallow nearshore environment. These forces are directly linked to microorganisms and the productivity of water bodies. While certain organisms exhibit adaptability across a broad range of conditions, others prove highly sensitive to environmental changes [31, 32]. So, during this direction, the present objective was to analyze the vital physico-chemical parameters (air temperature, surface water temperature, sediment temperature, water salinity, sediment salinity, water pH, sediment pH, electrical conductivity, DO, sediment nitrogen, potassium and phosphorus, TOC and soil texture) of the coastal wetland areas of the Havelock Island of the Andamans to find out their influence on the marine actinobacterial population density.

Generally, the surface water temperature will be influenced by solar radiation, evaporation, and freshwater influx [33]. Fluctuations in temperature can lead to significant changes in seawater properties, consequently affecting the life it sustains. Temperature variations contribute to alterations in water density, salinity, and dissolved oxygen levels. The growth and reproduction of aquatic life are also influenced by temperature-dependent processes [34]. Surface water temperature will be higher than that of the sediment temperature [35] because it decreases steadily from the surface to deep waters and sediments [3]. Supporting this view, in the present study, the air temperature was higher than that of the surface water and sediments in Havelock Island. This finding aligns with the research conducted by Ramaraju et al. [36], which documented a range of surface water temperatures from 27.5°C to 28.5°C in the southern Andaman Sea during winter and the study further noted a gradual decrease in temperature from the sea surface to depth. Statistically, air temperature showed a positive correlation with surface water temperature (r = 0.944, P < 0.01), sediment temperature (r = 0.817, P < 0.05), and sand (r = 0.756, P < 0.05).

Salinity is one of the most important factors that determine the composition of biological elements in the marine environment [37]. Salinity fluctuation would definitely affect the biological characteristics of the marine environment. In the present study, water salinity fluctuated from 18 to 35 psu and the salinity of the sediments fluctuated from 17 to 34 psu. Lower water and sediment salinity was found at station 4 and it could be due to the influence of freshwater prevailing in this mangrove creek area as compared to other stations. Maximum water and sediment salinity was found at station 6, which could be attributed to the high degree of evaporation and dominance of neritic waters, from the open sea [38]. Statistically, water salinity showed a positive correlation with sediment salinity (r = 0.992, P < 0.01) and sediment pH (r = 0.796, P < 0.05). Sediment salinity exhibited a positive correlation with sediment pH (r = 0.808, P < 0.05) and potassium content (r = 0.740, P < 0.05).

Water pH plays an important role by influencing all aquatic organisms, including microbes [39]. pH (water and sediments) values, ranging from 6 to 8 observed in the present study might favor the growth and survival of many types of microorganisms, as reported by Jay [40]. In the present study, sediment pH was higher (average 8.2) than that of water pH (average 7.4). In general, fluctuations in pH values are ascribed to factors, such as the removal of CO2 through photosynthesis via bicarbonate degradation, dilution of seawater due to freshwater influx, changes in salinity and temperature, and the decomposition of organic matter [41]. In addition, pH might often change with time due to temperature-salinity changes and biological activity [42]. Statistical analysis revealed that the water pH had a significant positive correlation with sediment pH (r = 0.922, P < 0.01).

DO concentration in water fluctuated from 4.60 to 2.10 ml l−1. Higher DO content was recorded at station 5, followed by station 6, due probably to the neritic influence. Lower dissolved oxygen concentration was recorded at station 1. This could be due to higher microbial utilization of DO. DO exhibited a negative correlation with both temperature and salinity. It is widely recognized that the dissolution of oxygen in seawater is influenced by variations in temperature and salinity [43].

EC is an indicator of higher concentrations of trace metals, which are capable of conducting electricity at much higher levels [44]. The range of EC was 1.7–6.4 dS m−1 in the post-tsunami period in the Andaman waters [45]. In the present study, EC of the sediments fluctuated from 2 to 5.5 dS m−1. Station 4 had higher EC level (5.5 dS m−1) as this station is a dense mangrove habitat with more decomposed soil and station 3 (sandy beach) had lower EC level (2 dS m−1). Swarnakumar [46] reported that based on the nature of the chemical characteristics of the soil, there will be significant variations in the EC.

In the present study, TOC content closely followed the sediment type, i.e., sediments low in clay content had lower amount of TOC and as the clay content increased, TOC content also increased, as reported by Reddy and Hariharan [47]. TOC value was lower at station 6. It was higher at station 4 followed by station 1, as these stations are mangrove habitats. Therefore, higher organic carbon content in the mangroves could be due to the mangrove and terrestrial detritus present in the suspended matter [48] and a higher rate of sedimentation, in addition to the fine nature of sediments (clayey and silt sediments) [49]. Decomposition of mangrove foliage and other vegetative remains in the sediments would also contribute to higher TOC [50]. Statistically, TOC exhibited a positive significant correlation with clay (r = 0.922, P < 0.01) and actinobacterial population density (r = 0.785, P < 0.05) and a negative significant correlation with sand (r = −0.872, P < 0.05).

Nutrients would promote the expansion and metabolic activity of the microbial communities within the marine environment [51]. This could be true in the coastal habitats of Havelock Island where sediments of nitrogen (2.63–10.88 mg g−1), phosphorus (3.13–4.50 mg g−1), and potassium (11.88–60.88 mg g−1) were recorded. Statistical analysis revealed that the sediment nitrogen content had a significant positive correlation with TOC (r = 0.906, P < 0.01), clay (r = 0.884, P < 0.01), and phosphorus (r = 0.777, P < 0.05). Phosphorus content also had a significant positive correlation with TOC (r = 0.936, P < 0.01) and clay (r = 0.905, P < 0.01).

Sediment soil texture also plays an important role in the distribution and abundance of marine microorganisms. A significant correlation between actinobacteria and clay fraction of the sediments has revealed a positive relationship between the microbes and sediments. Higher microbial population density mainly coexists with clayey sediments than the sandy sediments [52]. Similarly, in the present study, the actinobacterial population density was higher at station 4 followed by stations 5 and 1, which had more clay content. Correlation matrix also revealed that the sand content showed a negative significant correlation (r = −0.907, P < 0.01) whereas the clay content had a significant positive correlation (r = 0.932, P < 0.01). It is worth mentioning here that the clayey sediments would contain sufficient nutrients and organic matter content for the propagation of microbes, including actinobacteria [39].

In this investigation, hierarchical cluster analysis was employed to examine the similarities or differences among stations and physico-chemical parameters. The dendrogram, representing the analyzed stations and physico-chemical parameters, provides a visual overview of the clustering process (refer to Figures 13 and 14). The dendrogram revealed three distinct clusters. Cluster 1 aligns with station 4, Cluster 2 encompasses stations 3, 2, and 6, while Cluster 3 corresponds to stations 1 and 5 (Figure 13).

Figure 13.

Dendrogram of the cluster resemblance between physico-chemical parameters and six stations of the Havelock Island.

Figure 14.

Principal compound analysis plot of the physico-chemical parameters and actinobacterial population density recorded at six stations of the Havelock Island.

Cluster 1 (station 4) corresponds to a dense mangrove habitat with favorable physico-chemical conditions, supporting higher actinobacterial density, than the stations of the other clusters 2 and 3. In Cluster 2 (stations 3, 2, and 6), the station 3 clade showed a very close distance similarity with station 2 (8.929) and station 6 (9.599). These stations are coral and sandy habitats, having similar physico-chemical features. In the cluster 3 (stations 1 and 5), station 1 clade showed a close distance with station 5 (17.482), where there is the occurrence of monospecific stands of seagrasses (station 5) and station 1, occupied by patches of mangroves (station 1). Such a vegetated situation at stations 1 and 5 could be the reason for having similar physico-chemical features and actinobacterial density.

While the dendrogram can elucidate the structure of the dataset, it lacks the capacity to interpret the observed patterns in relation to the original parameters. To address this limitation, the dataset of target physico-chemical parameters underwent principal component analysis (PCA). This analytical approach was employed to ascertain which parameters significantly contribute to the variation in the actinobacterial density at the six stations of Havelock Island. PCA was utilized to discern trends among highly correlated physico-chemical parameters and microbial density, revealing a clear relationship between the stations and the physico-chemical parameters influencing actinobacterial population density.

In the PCA, a higher correlation component score was obtained between the actinobacterial population density and the physico-chemical parameters at station 4 (118), followed by station 1 (32.2) and station 5 (28.1). In the PC1 axis, these three stations had a positive significant correlation with clay, TOC, potassium (K), actinobacterial population density, nitrogen content, and EC. It could be due to the fact that these stations are occupied by mangroves (stations 4 and 1) and seagrasses (station 5). Whereas, stations 3, 2, and 6 had negative correlation component scores (−53, −57.3, and −68.2 respectively), thus proving that these three stations had a positive significant correlation with sand, phosphorus, and temperature. It could be ascribed to the fact that the two stations (stations 3 and 6) are sandy beaches and station 2 is a coral reef environment. In addition, at these three stations, very poor vegetation exists, as compared to stations 4 and 1 (mangrove habitats) and station 5 (seagrass habitat) (Figure 14).

Microbial populations can tolerate and grow under varying environmental conditions. During the present investigation, a higher population density of actinobacteria was recorded at station 4 in all tested media. Among these, Kuster’s agar medium showed higher numbers of actinobacterial colonies at all the stations. Similarly, previous literature also reported that Kuster’s agar was found to produce the desired level of actinobacterial colonies in the marine samples [26, 53, 54, 55, 56, 57]. Station 4, a dense mangrove habitat, had higher density of actinobacterial population since mangroves would act as a major nutrient transformation system, responsible for more microbial activity [58, 59]. Further, microbial colonies may emerge following the deposition of mangrove litter, proliferate rapidly, and attain substantial densities, actively contributing to both biomineralization and biotransformation processes of minerals [60, 61].

The density of actinobacterial populations is significantly influenced by sediment nutrients, especially total organic carbon [62] and actinobacteria, being saprophytic, thrive by relying on the availability of carbon [63]. Additionally, previous studies have also reported that the mangrove ecosystem is a potential spot to understand the actinobacterial community [56, 64, 65, 66]. Correlation matrix also showed that the actinobacterial population density had a positive significant correlation with clay (r = 0.932, P < 0.01), EC (r = 0.811, P < 0.05), nitrogen (r = 0.809, P < 0.05), P (r = 0.699, P < 0.05), and TOC (r = 0.785, P < 0.05) (Table 2).

ATSWTSTWSSSWpHSpHDOECNPKTOCSandSiltClayAPD
AT1
SWT0.944**1
ST0.817*0.6461
WS0.2790.0270.7231
SS0.214−0.0510.6960.992**1
WpH0.054−0.0970.3390.5410.5611
SpH0.210.0180.6080.796*0.808*0.922**1
DO−0.682−0.657−0.3680.2420.2540.440.3791
EC−0.356−0.195−0.359−0.39−0.37−0.824*−0.692−0.0651
N−0.372−0.132−0.721−0.942**−.0921**−0.735*−0.898**−0.2460.6651
P−0.603−0.38−0.692−0.761*−0.699−0.228−0.4330.1760.4770.777*1
K0.6060.4080.920**0.7290.740*0.1940.514−0.353−0.091−0.61−0.561
TOC−0.575−0.307−0.825*−0.906**−0.875*−0.436−0.6670.1130.530.906**0.936**−0.749*1
Sand0.759*0.5970.771*0.6810.6060.4390.58−0.167−0.681−0.810*−0.906**0.516−0.872*1
Silt−0.55−0.701−0.1240.1770.2950.3780.3360.290−0.0880.340.1470.06−0.4451
Clay−0.707−0.505−0.801*−0.763*−0.705−0.541−0.6840.1220.7280.884**0.905**−0.580.922**−0.986**0.2881
APD−.760*−0.598−0.820*−0.627−0.583−0.671−0.752*0.1850.811*0.809*0.699−0.570.785*−0.907**0.20.932**1

Table 2.

Pearson correlations coefficient (r) values of the actinobacterial population and physico-chemical characteristics of Havelock Island.

Correlation is significant at 5% level (P < 0.05).


Correlation is significant at 1% level (P < 0.01).


Air temperature (AT), surface water temperature (SWT), sediment temperature (ST), water salinity (WS), sediment salinity (SS), water pH (WpH), sediment pH (SpH), dissolved oxygen (DO), electrical conductivity (EC), nitrogen (N), phosphorus (P), potassium (K), total organic carbon (TOC), actinobacterial population density (APD).

At stations 5 and 1, there was a moderate population density of actinobacteria correlating with the occurrence of monospecific stands of seagrasses (station 5) and patches of mangroves (station 1), as revealed by the average cluster analysis, where both the stations fell under the same cluster (cluster 3). Next to the mangrove and seagrass habitats, station 2 (coral reef environment) recorded a fair actinobacterial population density. It could be possible because corals can secrete mucus, which makes up the surface mucopolysaccharide layer, a medium high in organic compounds, which constantly traps microbes of all varieties from seawater and develops a higher concentration of the community of bacteria than that of ambient seawater [67]. Stations 3 and 6, sandy beaches, with organic carbon content, 50–66.7% (lower than that of the muddy sediments), showed only a lower density of actinobacteria, compared to other habitats. In Hierarchical cluster analysis also, these three stations (3, 2, and 6) fell under the same cluster (cluster 2) with close resemblance distance.

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5. Conclusion

In conclusion, the present study has thus found that the physico-chemical parameters (air, surface water, and sediment temperatures, water and sediment salinity, water and sediment pH, electrical conductivity, dissolved oxygen, sediment nutrients, total organic carbon and soil texture) have influenced the actinobacterial population density directly or indirectly, in the different coastal habitats of the Havelock Island. The mangrove environment has favored higher density of actinobacteria than the other habitats. However, it should be noted that these environmental factors and their influence are specific and applicable only to the microbial populations of the study areas of the Havelock Island and should not be generalized. Additionally, information pertaining to the water quality parameters would help understand the present status of the coast of Havelock Island, which is now open for tourism. Hence, further in-depth studies comparing our study results will help understand the current stations of hydrographical features and actinobacterial density and diversity due to the latter’s ecosystems and biotechnology potentials.

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Acknowledgments

The authors express their gratitude to the Dean of the Faculty of Marine Sciences and the authorities of Annamalai University for generously providing the necessary facilities. Additionally, the Author (R.G) extends thanks to the Director and Joint Directors of SCERT, Chennai, as well as Dr. P. Natarajan, Principal of the District Institute of Education and Training, Pudukkottai, for their valuable support. It is important to note that the contents and views presented in this manuscript are those of the individual author and do not necessarily reflect the perspectives or positions of the respective institutions to which the author is affiliated.

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Credit authorship contribution

RG & KS: conceptualization, investigation, data curation, writing, original draft preparation, reviewing, and editing.

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Declaration of competing interest

The authors affirm that they do not have any known competing interests that might have influenced the work reported in this article.

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Data availability

The datasets utilized and examined in the present study can be obtained from the corresponding author upon reasonable request.

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Additional information

This work is an extended version of the doctoral thesis by the same author [R. Gobalakrishnan] and the title is Ecology, diversity and bioelectricity potential of Marine actinobacteria from The Havelock Island of the Andaman India. 2013, Unpublished doctoral thesis, Annamalai University, Available from: https://www.inflibnet.ac.in. And also, authors have full copyrights to use all the figures in this chapter.

References

  1. 1. Bakri DA, Kittaneh W. Physicochemical characteristics and pollution indicators in the intertidal zone of Kuwait: Implications for benthic ecology. Environmental Management. 1998;22:415-424. DOI: 10.1007/s002679900116
  2. 2. Cevera JH, Karl D, Buckley M. Marine Microbial Diversity: The Key to Earth’s Habitability. San Francisco, California: American Academic of Microbiology Colloquium Report; 2005. pp. 1-22
  3. 3. Das S, Lyla PS, Ajmalkhan S. Spatial variation of aerobic culturable heterotrophic bacterial population in sediments of the continental slope of western Bay of Bengal. Indian Journal of Geo-Marine Science. 2007;36:51-58. Available from: http://nopr.niscair.res.in/handle/123456789/14
  4. 4. Azam F, Fenchel T, Field JG, Gray JS, Meyer-Reil LA, Thingstad F. The ecological role of water column microbes in the sea. Marine Ecology Progress Series. 1983;10(3):257-263. DOI: 10.3354/meps010257
  5. 5. Ducklow HW, Hill S. The growth of heterotrophic bacteria in the surface waters of warm core rings. Limnology and Oceanography. 1985;30:239-259. DOI: 10.4319/lo.1985.30.2.0239
  6. 6. Alavandi SV. Relationship between heterotrophic bacteria and suspended particulate matter in the Arabian Sea. Indian Journal of Microbiology. 1990;30(1):89-92. Available from: https://krishi.icar.gov.in/jspui/bitstream/123456789/ 1155/1/05-1990%20Alavandi%20IJM.pdf
  7. 7. Dong H, Jiang H, Yu B, Liu X. Impacts of environmental change and human activity on microbial ecosystems on the Tibetan Plateau, NW China. GSA Today. 2010;20:4-10. DOI: 10.1130/GSATG75A.1
  8. 8. Duran R, Ranchou-Peyruse M, Menuet V, Monperrus M, Bareille G, Goni MS, et al. Mercury methylation by a microbial community from sediments of the Adour Estuary (Bay of Biscay, France). Environmental Pollution. 2008;156(3):951-958. DOI: 10.1016/j.envpol.2008.05.007
  9. 9. Thiyagarajan V, Lau SCK, Mandy T, Zhang W, Qian PY. Monitoring bacterial biodiversity in surface sediment using terminal restriction fragment length polymorphism analysis (T-RFLP): Application to coastal environment. In: Ishimatsu A, Lie HJ, editors. Coastal Environmental and Ecosystem Issues of the East China Sea. Nagasaki: Terrapub, Nagasaki University; 2010. pp. 151-163
  10. 10. Stevens H, Brinkhoff T, Rink B, Vollmers J, Simon M. Diversity and abundance of Gram positive bacteria in a tidal flat ecosystem. Environmental Microbiology. 2007;9:1810-1822. DOI: 10.1111/j.1462-2920.2007.01302.x
  11. 11. Mincer TJ, Jensen PR, Kauffman CA, Fenical W. Widespread and persistent populations of a major new marine actinomycete taxon in ocean sediments. Applied and Environmental Microbiology. 2002;68(10):5005-5011. DOI: 10.1128/AEM.68.10.5005-5011.2002
  12. 12. Maldonado LA, Stach JEM, Pathom-aree W, Ward AC, Bull AT, Goodfellow M. Diversity of cultivable actinobacteria in geographically widespread marine sediments. Antonie Van Leeuwenhoek. 2005;87:11-18. DOI: 10.1007/s10482-004-6525-0
  13. 13. Pathom-aree W, Stach JEM, Ward AC, Horikoshi K, Bull AT, Goodfellow M. Diversity of actinomycetes isolated from Challenger Deep sediment (10,898 m) from the Mariana Trench. Extremophiles. 2006;10:181-189. DOI: 10.1007/s00792-005-0482-z
  14. 14. Urakawa H, Tsukamoto KK, Ohwada K. Microbial diversity in marine sediments from Sagami Bay and Tokyo Bay, Japan, as determined by 16S rRNA gene analysis. Microbiology. 1999;145:3305-3315. DOI: 10.1099/00221287-145-11-3305
  15. 15. Bull AT, Stach JEM, Ward AC, Goodfellow M. Marine actinobacteria: Perspectives, challenges, future directions. Antonie Van Leeuwenhoek. 2005;87:65-79. DOI: 10.1007/s10482-004-6562-8
  16. 16. David S. Terrestrial ecosystem and carbon cycle. Global Change Biology. 2006;1(1):77-91. DOI: 10.1111/j.1365-2486.1995.tb00008.x
  17. 17. Ramesh S, William A. Marine actinomycetes: An ongoing source of novel bioactive metabolites. Microbiological Research. 2012;167(10):571-580. DOI: 10.1016/j.micres.2012.06.005
  18. 18. Sankar R, Ramkumar L, Rajkumar M, Sun J, Ananthan G. Seasonal variations in physico-chemical parameters and heavy metals in water and sediments of Uppanar estuary Nagapattinam India. Journal of Environmental Biology. 2010;31(5):681-686. Available from: https://pubmed.ncbi.nlm.nih.gov/21387922/
  19. 19. Jayaraj KA, Jayalakshmi KV, Saraladevi K. Influence of environmental properties on macrobenthos in the Northwest Indian shelf. Environmental Monitoring and Assessment. 2007;127:459-475. DOI: 10.1007/s10661-006-9295-5
  20. 20. Reddi KR, Jayaraju N, Suriyakumar I, Sreenivas K. Tidal fluctuation in relation to certain physio-chemical parameters in Swarnamukhi river estuary, East coast of India. Indian Journal of Geo-Marine Sciences. 1993;22:232-234. Available from: http://nopr.niscair.res.in/handle/123456789/37883
  21. 21. Strickland JDH, Parsons TR. A Practical Handbook of Seawater Analysis, Bulletin. Vol. 167. Ottawa: Fisheries Research Board of Canada; 1972
  22. 22. Subbiah BV, Asija GL. A rapid procedure for estimation of available nitrogen in soils. Current Science. 1956;25:259-260
  23. 23. Olsen SR, Cole CV, Watanabe FS. Estimation of Available Phosphorus in Soil by Extraction with Sodium Bicarbonate, Circular, No. 939. Washington, DC: United States Department of Agriculture; 1954
  24. 24. El-Wakeel SK, Riley JP. The determination of organic carbon in marine mud. ICES Journal of Marine Science. 1956;22(2):180-183. DOI: 10.1093/icesjms/22.2.180
  25. 25. Lindholem RC. A Practical Approach to Sedimentology. Netherlands: Springer; 1987. DOI: 10.1007/978-94-011-7683-5
  26. 26. Gobalakrishnan R. Phylogenetic diversity of culturable marine actinobacteria isolated from the Havelock Island, the Andamans, India. Ecological Genetics and Genomics. 2023;100123:1-8. DOI: 10.1016/j.egg.2022.100123
  27. 27. Gobalakrishnan R, Sivakumar L. Systematic characterization of potential cellulolytic marine actinobacteria Actinoalloteichus sp. MHA15. Biotechnology Reports. 2017;13:30-36. DOI: 10.1016/j.btre.2016.12.003
  28. 28. Anupama S, Aishwarya T, Anupa B, Muskan S, Prativa S, Sagar A. Isolation, characterization and screening of antimicrobial producing actinomycetes from soil samples. International Journal of Microbiology. 2020;2020:1-7. Article ID: 2716584. DOI: 10.1155/2020/2716584
  29. 29. Abdenbi El K, Soumia AA, Mohammed EH. Isolation and screening of actinomycetes producing antimicrobial substances from an extreme Moroccan biotope. The Pan African Medical Journal. 2019;33(329):1-9. DOI: 10.11604/pamj.2019.33.329.19018
  30. 30. Waksman SA. Strain specificity and production of antibiotic substances. Characterization and classification of species within the Streptomyces griseus group. Proceedings of the National Academy of Sciences of the United States of America. 1959;45(7):1043-1047. DOI: 10.1073/pnas.45.7.1043
  31. 31. Rusch A, Huettel M, Reimers CE, Taghon GL, Fuller CM. Activity and distribution of bacterial populations in Middle Atlantic Bight shelf sands. FEMS Microbiology Ecology. 2003;44:89-100. DOI: 10.1111/j.1574-6941.2003.tb01093.x
  32. 32. Raibole M, Singh YP. Impact of physico-chemical parameters on microbial diversity: Seasonal study. Current World Environment: An International Research Journal of Environmental Science. 2011;6:71-76. DOI: http://dx.doi.org/10.12944/CWE.6.1.09
  33. 33. Ajithkumar TT, Thangaradjou T, Kannan L. Physico-chemical and biological properties of the Muthupettai mangrove in Tamil Nadu. The Marine Biological Association of India. 2006;48:131-138
  34. 34. Davis RA. Principles of Oceanograph. 2nd ed. New York: Addison - Wesley Publishing; 1977
  35. 35. Muraleedharan H, Abhilash R. Physico-chemical parameters and planktons analysis of sea water of Thondi of Palk Bay, Tamilnadu. Journal of Biological Science Research. 2010;1(1):20-24
  36. 36. Ramaraju DV, Gouveia AD, Murthy CS. Some physical characteristic of Andaman Sea waters during winter. Indian Journal of Geo-Marine Science. 1981;10:211-218. Available from: http://nopr.niscair.res.in/handle/123456789/39079
  37. 37. Manivasagan P. Ecology, taxonomy and biological potential (antibiotic, pigment and enzyme) of marine actinobacteria from the Tamilnadu part of Bay of Bengal, India [Ph.D. thesis]. India: Annamalai University; 2009
  38. 38. Senthilkumar S, Santhanam P, Perumal P. Diversity of phytoplankton in Vellar estuary, Southeast coast of India. In: Ayyappan S, Jena JK, Mohan Joseph M, editors. AAFSIB (Asian Fisheries Society Indian Branch), Mangalore and AoA (Association of Aquaculturists), Bhubaneswar, India. 2002. pp. 245-248
  39. 39. Gnanam S, Sivakumar K, Vijayalakshmi S, Balasubramaniyan T. Ambience of physico-chemical characteristics to actinobacterial density in the Chennai coast of the Bay of Bengal, India. Indian Journal of Geo-Marine Science. 2013;42:254-265. Available from: http://nopr.niscair.res.in/handle/123456789/16948
  40. 40. Jay JM. Modern Food Microbiology. 5th ed. New York: Van Norstrand Reinhold; 1996
  41. 41. Rajasegar M. Physico-chemical characteristics of the Vellar estuary in relation to shrimp farming. Journal of Environmental Biology. 2003;24(1):95-101
  42. 42. Srilatha G, Thilagavathi B, Varadharajan D. Studies on the physico-chemical status of Muthupettai mangrove, South east coast of India. Advances in Applied Science Research. 2012;3(1):201-207
  43. 43. Vijayakumar SK, Rajesh KM, Mendon MR, Hariharan V. Seasonal distribution and behaviour of nutrients with reference to tidal rhythm in the Mulki estuary, southwest coast of India. Journal of the Marine Biological Association of India. 2000;42(1&2):21-31. Available from: http://mbai.org.in/uploads1/manuscripts/Chpater_02%20(21-31)1856714598.pdf
  44. 44. Chaudhuri GS, Dinesh R, Sheeja TE, Raja R, Jeykumar V, Srivastava RC. Physico-chemical, biochemical and microbial characteristics of soils of mangroves of the Andamans: A post-tsunami analysis. Current Science. 2009;97:98-102. Available from: https://www.jstor.org/stable/24112089
  45. 45. Nayak AK, Damodaran T, Singh CS, Jha SK, Raja D, Mishra VK, et al. Post tsunami changes in soil properties of Andaman islands India. Environmental Monitoring and Assessment. 2010;170:185-193. DOI: 10.1007/s10661-009-1225-x
  46. 46. Swarnakumar NS. Studies on the actinobacteria of the coastal environment of Nicobar group of islands with special reference to anticancer properties [Ph.D. thesis]. India: Annamalai University; 2010
  47. 47. Reddy HRV, Hariharan V. Distribution of nutrients in the sediments of the Netravathi-Gurupur estuary, Mangalore. Indian Journal of Fisheries. 1986;33(1):123-126
  48. 48. Jagtap TG. Seasonal distribution of organic matter in mangrove environment of Goa. Indian Journal of Geo-Marine Science. 1987;16:103-106
  49. 49. Raghunath R, Sreedhara Murthy TR. Carbonate and organic matter studies of the shelf of Kasargod, west coast of India. Indian Journal of Geo-Marine Science. 1996;25:355-357. Available from: http://nopr.niscair.res.in/handle/123456789/37152
  50. 50. Ramanathan AL. Sediment characteristics of the Pichavaram mangrove environment, Southeast coast of India. Indian Journal of Geo-Marine Science. 1997;26:319-322. Available from: http://nopr.niscair.res.in/handle/123456789/36329
  51. 51. Trupti KV, Dave BP. Effect of addition of nitrogen, phosphorus and potassium fertilizers on biodegradation of crude oil by marine bacteria. Indian Journal of Geo-Marine Science. 2010;39:143-150. Available from: http://nopr.niscair.res.in/handle/123456789/8558
  52. 52. Nair SL, Bharathi PA, Achuthankutty CT. Distribution of heterotrophic bacteria in marine sediments. Indian Journal of Geo-Marine Science. 1978;7:18-22
  53. 53. Saadoun I, Al-momani F. Bacterial and Streptomyces flora of some Jordan valley soils. Actinomycetes. 1996;7:95-99. Available from: http://hdl.handle.net/1807/22671
  54. 54. Raghavendrudu G, Kondalarao B. Studies on the distribution of actinobacteria in the Gaderu mangroves of Gautami Godavari estuarine system, East coast of India. Journal of the Marine Biological Association of India. 2007;49:246-249. Available from: http://mbai.org.in/php/journaldload.php?id=2041&bkid=93
  55. 55. Baskaran R, Vijayakumar R, Mohan PM. Enrichment method for the isolation of bioactive actinomycetes from mangrove sediments of Andaman islands, India. Malaysian Society for Microbiology. 2011;7:26-32
  56. 56. Sethubathi GVB, Sivakumar K, Thangaradjou T, Kannan L. Ecology and population density of the marine actinobacteria of little Andaman island India. Indian Journal of Geo-Marine Science. 2013;42:390-401. Available from: http://nopr.niscair.res.in/handle/123456789/19653
  57. 57. Gobalakrishnan R, Bhuvaneswari R. Microbial fuel cells potential of marine actinobacteria Actinoalloteichus sp. MHA15 from the Havelock Island of the Andamans, India. Biotechnology Research and Innovation. 2019;3(1):144-158. DOI: 10.1016/j.biori.2019.01.003
  58. 58. Alongi DM, Christoffersen P, Tirendi F. The influence of forest type on microbial nutrient relationships in tropical mangrove sediments. Journal of Experimental Marine Biology and Ecology. 1993;171(2):201-223. DOI: 10.1016/0022-0981(93)90004-8
  59. 59. Holguin G, Vazquez P, Bashan Y. The role of sediment microorganisms in the productivity, conservation, and rehabilitation of mangrove ecosystems: An overview. Biology and Fertility of Soils. 2001;33:265-278. DOI: 10.1007/s003740000319
  60. 60. Kathiresan K. Degradation and destruction of mangroves. In: Kathiresan K, Ajmal Khan S, editors. International Training Course on Coastal Biodiversity in Mangroves Ecosystems. India: UNU-INWEH-UNESCO; 2007. pp. 476-483
  61. 61. Gonzalez-Acosta B, Bashan Y, Hernandez-Saavedra NY, Ascenaio F, Cruz Aguero G. Seasonal seawater temperature as the major determinant for populations of culturable bacteria in the soils of an in-tact mangrove in an Arid region. FEMS Microbiology Ecology. 2006;55:311-321. DOI: 10.1111/j.1574-6941.2005.00019.x
  62. 62. Das S, Lyla P, Ajmalkhan S. Distribution and generic composition of culturable marine actinomycetes from the marine sediments of continental slope of Bay of Bengal. Chinese Journal of Oceanology and Limnology. 2008;26:166-177. DOI: 10.1007/s00343-008-0166-5
  63. 63. Promod KC, Dhevendaran K. Studies on phosphobacteria in Cochin backwater. Journal of the Marine Biological Association of India. 1987;29(1&2):297-305
  64. 64. Karthikeyan P, Senthilkumar G, Panneerselvam A. Actinobacterial diversity of mangrove environment of the Palaverkadu mangroves, East Coast of Tamilnadu, India. International Journal of Current Microbiology and Applied Sciences. 2014;3:145-154. Available from: http://www.ijcmas.com/vol-3-1/P.Karthikeyan%20G.Senthilkumar%20and%20A.Panneerselvam.pdf
  65. 65. Mangamuri UK, Vijayalakshmi M, Sudhakar P. Exploration of actinobacteria from mangrove ecosystems of Nizampatnam and Coringa for antimicrobial compounds and industrial enzymes. Biotechnology Journal International. 2014;4:173-184. DOI: 10.9734/BBJ/2014/6424
  66. 66. Poongodi S, Sivakumar K, Sivasankar P, Kannan L. Ecological factors and their influence on actinobacterial density from different coastal habitats of Neil island, Andamans. Indian Journal of Geo-Marine Sciences. 2016;45(07):911-919. Available from: http://nopr.niscair.res.in/handle/123456789/35137
  67. 67. Ritchie KB. Regulation of microbial population by coral surface mucus and mucus-associated bacteria. Marine Ecology Progress Series. 2006;322:1-14. DOI: 10.3354/meps322001

Written By

Rajagopal Gobalakrishnan and Kannan Sivakumar

Submitted: 10 January 2024 Reviewed: 27 February 2024 Published: 29 October 2024

© 2024 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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